Measuring the Temporal Dimension of Text: An Application to Policymaker Speeches

David Byrne, Robert Goodhead, Michael McMahon and Conor Parle
Additional contact information
Robert Goodhead: Central Bank of Ireland

No 2/RT/23, Research Technical Papers from Central Bank of Ireland

Abstract: Discussions of time are central to many questions in the social sciences and to official announcements of policy. Despite the growing popularity of applying Natural Language Processing (NLP) techniques to social science research questions, before now there have been few attempts to measure expressions of time. This paper provides a methodology to measure the “third T of Text”: the Time dimension. We also survey the techniques used to measure the other Ts, namely Topic and Tone. We document key stylised facts relating to temporal information in a corpus of policymaker speeches.

Keywords: Textual analysis; Machine Learning; Communication. (search for similar items in EconPapers)
JEL-codes: C55 C80 E58 (search for similar items in EconPapers)
Date: 2023-02
New Economics Papers: this item is included in nep-big, nep-cmp and nep-mon
References: Add references at CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
https://www.centralbank.ie/docs/default-source/pub ... df?sfvrsn=9469991d_5 (application/pdf)

Related works:
Working Paper: Measuring the Temporal Dimension of Text: An Application to Policymaker Speeches (2023)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:cbi:wpaper:2/rt/23

Access Statistics for this paper

More papers in Research Technical Papers from Central Bank of Ireland Contact information at EDIRC.
Bibliographic data for series maintained by Fiona Farrelly ().